Hate Speech Hashtag Classification Using Hybrid Artificial Neural Network (ANN) Method

Authors

  • Lintang Aryasatya Telkom University, Bandung
  • Yuliant Sibaroni Telkom University, Bandung

DOI:

https://doi.org/10.30865/jurikom.v9i4.4425

Keywords:

Twitter, Hate Speech, Hybrid Aritificial Neural Network (ANN), Classification, Social Networking

Abstract

Social networking sites Twitter is frequently used as a platform for information gathering various communities/forums as well as individuals to discuss certain things. Dissemination of information on Twitter can be in the form of positive information and negative information. One of the negative information is hate speech contained in the form of hashtags on twitter. Hate Speech Hashtag Classification was be carried out using the Hybrid Artificial Neural Network (ANN) method to produce satisfactory results compared to previous methods such as KNN and so on because the large amount of data in Twitter will be very profitable and produce good accuracy when using Hybrid Learning, Hybrid Learning with 5 Cross Validation the highest accuracy is 79% , the lowest is 73%, the average accuracy is 76%.

References

J. C. Pereira-Kohatsu, L. Quijano-Sánchez, F. Liberatore, And M. Camacho-Collados, “Detecting And Monitoring Hate Speech In Twitter,†Sensors, Vol. 19, No. 21, P. 4654, 2019, Doi: 10.3390/S19214654.

M. Yoosefi Nejad, M. S. Delghandi, A. O. Bali, And M. Hosseinzadeh, “Using Twitter To Raise The Profile Of Childhood Cancer Awareness Month,†Netw. Model. Anal. Heal. Informatics Bioinforma., Vol. 9, No. 1, Pp. 1–5, 2020, Doi: 10.1007/S13721-019-0206-4.

E. Fehn Unsvåg And B. Gambäck, “The Effects Of User Features On Twitter Hate Speech Detection,†In Proceedings Of The 2nd Workshop On Abusive Language Online (Alw2), 2018, Pp. 75–85. Doi: 10.18653/V1/W18-5110.

B. Y. Pratama And R. Sarno, “Personality Classification Based On Twitter Text Using Naive Bayes, Knn And Svm,†In 2015 International Conference On Data And Software Engineering (Icodse), 2015, Pp. 170–174. Doi: 10.1109/Icodse.2015.7436992.

A. Al-Hassan And H. Al-Dossari, “Detection Of Hate Speech In Arabic Tweets Using Deep Learning,†Multimed. Syst., Pp. 1–12, Jan. 2021, Doi: 10.1007/S00530-020-00742-W.

A. Briliani, “Deteksi Ujaran Kebencian Dalam Bahasa Indonesia Pada Kolom Komentar Instagram Dengan Metode Klasifikasi K-Nearest Neighbor,†2019.

A. Fadilah, “Penerapan Algoritma K-Nearest Neighbor Untuk Mendeteksi Ujaran Kebencian Dan Bahasa Kasar Pada Twitter Bahasa Indonesia.†Universitas Islam Negeri Sultan Syarif Kasim Riau, 2021.

U. S. A. Rahman, Y. Wibisono, And E. P. Nugroho, “Implementasi Multinomial Naive Bayes Untuk Klasifikasi Ujaran Kebencian Pada Dataset Kicauan (Twitter) Bahasa Indonesia,†J. Apl. Dan Teor. Ilmu Komput., Vol. 3, No. 2.

J. Salminen, M. Hopf, S. A. Chowdhury, S. Jung, H. Almerekhi, And B. J. Jansen, “Developing An Online Hate Classifier For Multiple Social Media Platforms,†Human-Centric Comput. Inf. Sci., Vol. 10, No. 1, P. 1, Dec. 2020, Doi: 10.1186/S13673-019-0205-6.

F. E. Ayo, O. Folorunso, F. T. Ibharalu, I. A. Osinuga, And A. Abayomi-Alli, “A Probabilistic Clustering Model For Hate Speech Classification In Twitter,†Expert Syst. Appl., Vol. 173, P. 114762, Jul. 2021, Doi: 10.1016/J.Eswa.2021.114762.

R. Martins, M. Gomes, J. J. Almeida, P. Novais, And P. Henriques, “Hate Speech Classification In Social Media Using Emotional Analysis,†In 2018 7th Brazilian Conference On Intelligent Systems (Bracis), Oct. 2018, Pp. 61–66. Doi: 10.1109/Bracis.2018.00019.

G. Rizos, K. Hemker, And B. Schuller, “Augment To Prevent: Short-Text Data Augmentation In Deep Learning For Hate-Speech Classification,†In Proceedings Of The 28th Acm International Conference On Information And Knowledge Management, Nov. 2019, Pp. 991–1000. Doi: 10.1145/3357384.3358040.

H. Sahi, Y. Kilic, And R. B. Saglam, “Automated Detection Of Hate Speech Towards Woman On Twitter,†In 2018 3rd International Conference On Computer Science And Engineering (Ubmk), Sep. 2018, Pp. 533–536. Doi: 10.1109/Ubmk.2018.8566304.

B. Y. Pratama And R. Sarno, “Personality Classification Based On Twitter Text Using Naive Bayes, Knn And Svm,†In 2015 International Conference On Data And Software Engineering (Icodse), Nov. 2015, Pp. 170–174. Doi: 10.1109/Icodse.2015.7436992.

J. Kaur And A. Kalra, “Hybrid Artificial Neural Network For Data Classification Problem,†In 2017 4th International Conference On Signal Processing, Computing And Control (Ispcc), Sep. 2017, Pp. 66–71. Doi: 10.1109/Ispcc.2017.8269651.

I. Kamalludin And B. N. Arief, “Kebijakan Formulasi Hukum Pidana Tentang Penanggulangan Tindak Pidana Penyebaran Ujaran Kebencian (Hate Speech) Di Dunia Maya,†Law Reform, Vol. 15, No. 1, P. 113, May 2019, Doi: 10.14710/Lr.V15i1.23358.

T. Ridwansyah, “Implementasi Text Mining Terhadap Analisis Sentimen Masyarakat Dunia Di Twitter Terhadap Kota Medan Menggunakan K-Fold Cross Validation Dan Naïve Bayes Classifier,†Klik Kaji. Ilm. Inform. Dan Komput., Vol. 2, No. 5, Pp. 178–185, Apr. 2022, Doi: 10.30865/Klik.V2i5.362.

Fatri Nurul Inayah, Sri Suryani Prasetiyowati, And Yuliant Sibaroni, “Classification Of Dengue Hemorrhagic Fever (Dhf) Spread In Bandung Using Hybrid Naïve Bayes, K-Nearest Neighbor, And Artificial Neural Network Methods,†Int. J. Inf. Commun. Technol., Vol. 7, No. 1, Pp. 10–20, Jun. 2021, Doi: 10.21108/Ijoict.V7i1.562.

Additional Files

Published

2022-08-30

How to Cite

Aryasatya, L., & Sibaroni, Y. (2022). Hate Speech Hashtag Classification Using Hybrid Artificial Neural Network (ANN) Method. JURNAL RISET KOMPUTER (JURIKOM), 9(4), 784–789. https://doi.org/10.30865/jurikom.v9i4.4425